Javier López-Santiago

11 papers Journal 10Unranked 1
YearRankTypeTitle / Venue / Authors
2025 J jnl
Data-driven informative priors for Bayesian inference with quasi-periodic data.
CoRR
Javier López-Santiago, Luca Martino, Joaquín Míguez, Gonzalo Vazquez-Vilar
2024 J jnl
Maximum likelihood inference for a class of discrete-time Markov switching time series models with multiple delays.
EURASIP J. Adv. Signal Process.
José. A. Martínez-Ordoñez, Javier López-Santiago, Joaquín Míguez
2023 J jnl
Marginal Likelihood Computation for Model Selection and Hypothesis Testing: An Extensive Review.
SIAM Rev.
Fernando Llorente, Luca Martino, David Delgado, Javier López-Santiago
2021 J jnl
Automatic tempered posterior distributions for Bayesian inversion problems.
CoRR
Luca Martino, Fernando Llorente, Ernesto Curbelo, Javier López-Santiago, Joaquín Míguez
2021 J jnl
Compressed Particle Methods for Expensive Models With Application in Astronomy and Remote Sensing.
IEEE Trans. Aerosp. Electron. Syst.
Luca Martino, Víctor Elvira, Javier López-Santiago, Gustau Camps-Valls
2021 J jnl
Compressed particle methods for expensive models with application in Astronomy and Remote Sensing.
CoRR
Luca Martino, Víctor Elvira, Javier López-Santiago, Gustau Camps-Valls
2020 J jnl
Adaptive Quadrature Schemes for Bayesian Inference via Active Learning.
IEEE Access
Fernando Llorente-Fernández, Luca Martino, Victor Elvira, David Delgado, Javier López-Santiago
2020 J jnl
Adaptive quadrature schemes for Bayesian inference via active learning.
CoRR
Fernando Llorente, Luca Martino, Víctor Elvira, David Delgado, Javier López-Santiago
2020 J jnl
Marginal likelihood computation for model selection and hypothesis testing: an extensive review.
CoRR
Fernando Llorente, Luca Martino, David Delgado, Javier López-Santiago
2020 — conf
On the computation of marginal likelihood via MCMC for model selection and hypothesis testing.
EUSIPCO
Fernando Llorente, Luca Martino, David Delgado-Gómez, Javier López-Santiago
2011 J jnl
YouASTRO: a web-based bibliography management system with distributed comments and rating features for SAO/NASA ADS papers
CoRR
Fabrizio Bocchino, Javier López-Santiago, Juan F. Albacete-Colombo, Niccolò Bucciantini